Relying on past achievements is not advisable; the cryptocurrency field cannot establish a sustainable moat through network effects alone.
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Relying on past achievements is not advisable; the cryptocurrency field cannot establish a sustainable moat through network effects alone.
A project must continuously "take action" to gain market recognition.
Navigating Web3 tides with focused insightsAuthor: Catrina, Crypto KOL
Translation: Felix, PANews
Re-examining Web2’s most popular Growth Hacking—Why network effects are no longer a durable moat in Web3.
First, let's understand the definition of network effects and why they matter in Web2. The following results are from ChatGPT:
Definition: A network effect occurs when a product or service gains additional value as more people use it. This means each new user increases the overall value of the product or service for existing users.
Benefits of Network Effects (NE):
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Strengthen competitive moats—More users make the product more valuable, thus deterring competitors.
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Reduce user acquisition costs—Existing users attract new users through word-of-mouth, integrations, or ecosystem effects.
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Create higher switching costs and retention rates—As the network grows, users become increasingly embedded in the ecosystem (e.g., social connections, data, integrations). Leaving becomes costly or inconvenient, improving retention and pricing power.
Some may object here, but this article emphasizes that network effects are not a durable moat in crypto. Due to the following characteristics of cryptocurrency, they cannot provide crypto companies with the same level of durability and sustainable competitive advantage as Web2 companies enjoy.
Trait 1: Crypto users are often more profit-driven
Developers as users: Developers are users/buyers of blockchains (L1s, L2s, other "layers"). Blockchains offer developers similar products: blockspace within an immutable on-chain database that records transaction history. When choosing where to build, developers typically share common criteria:
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Lowest transaction fees
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Fastest transaction processing
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Highest liquidity
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Strongest ecosystem/community support, including grants
As shown in Electric Capital's developer report above, Ethereum initially benefited from network effects, attracting most developers to build exclusively on Ethereum ("single-chain developers"). However, faced with competitors like Solana and Base, network effects failed to save Ethereum, which suffered from poor performance and fragmented liquidity. Since 2022, the ratio of "single-chain developers" to "total monthly active developers" has dropped sharply. This shift reveals developers’ profit-driven nature—they move toward environments that best meet their needs rather than staying out of loyalty.
Retail users as users: As long as DeFi remains the primary use case in crypto, liquidity providers and DeFi users will continue seeking:
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Highest liquidity yields
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Lowest slippage in trades
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Broadest selection of tokens
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Most attractive farming rewards
This behavior is often unrelated to user experience or platform preference.
Moreover, wallets enable seamless and effortless switching between platforms such as Uniswap and Hyperliquid.
Validators as users: Validators naturally seek the highest nominal value in block rewards—whether from their staked assets (in PoS networks) or from services provided (as DePIN providers).
The decision to continue using or supporting alternative L1s, L2s, app-chains, or DePIN projects comes down to simple cost-benefit calculations. Validators evaluate economic value and the sustainability of block rewards when making these decisions.
Trait 2: Cryptocurrencies are open-source by default, drastically lowering the barrier to imitation
"Vampire attacks": SushiSwap copied Uniswap’s code, offered an identical user experience, then introduced more profitable token incentives to siphon off Uniswap’s liquidity providers and users.
Executing a similar attack in Web2 would be far more difficult. One would need to steal Facebook’s entire codebase, launch an equivalent or better product, and then fund incentives for all Facebook users to migrate to the new platform.
Trait 3: Cryptocurrencies are interoperable by default, minimizing switching costs for developers and retail users
Take USDC as an example—it could arguably have the strongest network effect in crypto. Compare it to one of its Web2 counterparts, the Visa network. If USDC isn’t accepted, users can exchange it for USDT, USDe, or PYUSD on a DEX or CEX with minimal time and effort.
However, switching from a Visa card to a Mastercard is significantly more cumbersome for users.
Returning now to the main argument of this article: Why network effects do not grant crypto companies the same advantages as their Web2 peers:
Network effects don't strengthen competitive moats: Due to the forkability and open-source nature of crypto, combined with Bertrand competition (PANews note: where products across different firms are perfect substitutes, so the firm with the lower price captures the entire market while higher-priced ones gain nothing) between undifferentiated offerings (yield, blockspace, liquidity), network effects don’t necessarily make early movers with more users inherently “more competitive.”
Network effects don’t reduce the cost of acquiring crypto users: Crypto users—both retail and developer—are fundamentally more profit-driven than Web2 users. Retail users chase optimal trading outcomes and yield returns. Developers favor the best performance and deepest liquidity. Regardless of network effects, liquidity will remain in an ecosystem as long as yields are profitable for LPs.
Some even argue that crypto exhibits anti-network effects: The more LPs in a pool, the lower the yields; the more users on a chain, the higher the fees and congestion.
Network effects don’t create higher switching costs or retention in crypto: Thanks to blockchain’s inherent composability and interoperability, switching costs in crypto are extremely low.
Crypto also lacks data moats. No on-chain data can be considered “proprietary,” which contrasts sharply with big tech companies whose exclusive data is key to retaining users.
Finally, consider a case study on Ethereum, widely regarded as the epitome of network effects in crypto. Since being dubbed the “world computer,” Ethereum combined blockchain innovation with programmable money and benefited from early network effects:
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Developer adoption: Ethereum attracted the largest community of blockchain developers early on, primarily because its EVM became the industry standard for initial blockchain development.
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Liquidity and DeFi dominance: Ethereum hosted the majority of crypto liquidity via DeFi platforms—until recently overtaken by Solana. More liquidity attracted more users → easier, cheaper trading/lending → even more liquidity.
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Security: Increased usage strengthened Ethereum’s security, attracting more projects and users.
Yet this trend broke this year. Ethereum squandered its strong starting position: delaying product improvements and over-fragmenting its ecosystem by supporting L2s that eroded its own liquidity. This led to:
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Massive developer outflow: Monthly active developers declined by 17% in 2024, while Solana saw new developer growth of approximately 83%.
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Liquidity outflow: According to DeFiLlama data, Ethereum’s DeFi dominance fell from 100% to 50%.
And Ethereum’s supposed network effects were unable to reverse this trend.
In contrast, despite similar lapses in innovation and execution, Web2 giants like Meta and Twitter continue to dominate their respective markets effortlessly. Why? Because network effects in Web2 actually work and are durable:
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Competitors cannot fork their code and offer similar products.
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Data on Twitter and Facebook is truly proprietary and irreplaceable.
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They cannot interoperate with any external projects outside their own ecosystems.
Given these factors, traditional network effects that provide long-term moats for Web2 companies simply do not apply in crypto.
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